Navigating multi-way stop intersections with an autonomous vehicle

ABSTRACT

The subject matter described in this specification is directed to a system and techniques for operating an autonomous vehicle (AV) at a multi-way stop intersection. After detecting the AV is at a primary stopline of the multi-way stop intersection, a planned travel path though the multi-way stop intersection is obtained. If the planned travel path of the AV through the multi-way stop intersection satisfies a set of one or more clearance criteria, the AV proceeds past the primary stopline. The clearance criteria include a criterion that is satisfied in response to detecting the AV is clear to safely merge into a travel lane corresponding to the planned travel path.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional PatentApplication No. 62/912,417, filed Oct. 8, 2019, entitled “NAVIGATINGMULTI-WAY STOP INTERSECTIONS WITH AN AUTONOMOUS VEHICLE,” the entirecontents of which are hereby incorporated by reference.

FIELD

This description relates to autonomous vehicles, and more specificallyto autonomous vehicles navigating multi-way stop intersections.

BACKGROUND

Autonomous vehicles can be used to transport people and/or cargo (e.g.,packages, objects, or other items) from one location to another. Forexample, an autonomous vehicle can navigate to the location of a person,wait for the person to board the autonomous vehicle, and navigate to aspecified destination (e.g., a location selected by the person). Tonavigate in the environment, these autonomous vehicles are equipped withvarious types of sensors to detect objects in the surroundings.

SUMMARY

The subject matter described in this specification is directed to asystem and techniques for navigating an autonomous vehicle through amulti-way stop intersection. Generally, the system is configured toinstruct the autonomous vehicle to wait at a stopline of the multi-waystop intersection until it is safe for the autonomous vehicle to proceedpast the stopline.

In particular, an example technique includes: while a first vehicle isoperating in an autonomous mode: detecting, using a processing circuit,the first vehicle is at a primary stopline of a multi-way stopintersection; obtaining, using the processing circuit, a planned travelpath though the multi-way stop intersection; and in response todetecting that the first vehicle is at a primary stopline of a multi-waystop intersection: in accordance with a determination that the plannedtravel path of the first vehicle through the multi-way stop intersectionsatisfies a set of one or more clearance criteria, instructing, using acontrol circuit, the first vehicle to proceed past the primary stopline,wherein the set of one or more clearance criteria include a criterionthat is satisfied in response to detecting the first vehicle is clear tosafely merge into a travel lane corresponding to the planned travelpath; and in accordance with a determination that the planned travelpath of the first vehicle through the multi-way stop intersection doesnot satisfy the set of one or more clearance criteria, instructing,using the control circuit, the first vehicle to forgo proceeding pastthe primary stopline.

Another example technique includes: while a first vehicle is operatingin an autonomous mode at a multi-way stop intersection and has a highestprecedence at the multi-way stop intersection: detecting, using aprocessing circuit, movement of a second vehicle at the intersection,the second vehicle having an expected travel path through theintersection that intersects a planned travel path of the first vehiclethrough the intersection; and in accordance with a determination, basedon the detected movement of the second vehicle, that the second vehicleis expected to exit the intersection, instructing, using a controlcircuit, the first vehicle to proceed into the intersection before thesecond vehicle exits the intersection.

These and other aspects, features, and implementations can be expressedas methods, apparatuses, systems, components, program products, means orsteps for performing a function, and in other ways.

These and other aspects, features, and implementations will becomeapparent from the following descriptions, including the claims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows an example of an autonomous vehicle having autonomouscapability.

FIG. 2 illustrates an example “cloud” computing environment.

FIG. 3 illustrates a computer system.

FIG. 4 shows an example architecture for an autonomous vehicle.

FIG. 5 shows an example of inputs and outputs that may be used by aperception module.

FIG. 6 shows an example of a LiDAR system.

FIG. 7 shows the LiDAR system in operation.

FIG. 8 shows the operation of the LiDAR system in additional detail.

FIG. 9 shows a block diagram of the relationships between inputs andoutputs of a planning module.

FIG. 10 shows a directed graph used in path planning.

FIG. 11 shows a block diagram of the inputs and outputs of a controlmodule.

FIG. 12 shows a block diagram of the inputs, outputs, and components ofa controller.

FIGS. 13A-13L illustrate examples of an autonomous vehicle navigating amulti-way stop intersection.

FIG. 14 is a flow chart of an example process for navigating a multi-waystop intersection.

FIG. 15 is a flow chart of another example process for navigating amulti-way stop intersection.

DETAILED DESCRIPTION

In the following description, for the purposes of explanation, numerousspecific details are set forth. It will be apparent, however, that someembodiments may be practiced without these specific details. In otherinstances, well-known structures and devices are shown in block diagramform in order to avoid unnecessarily obscuring the describedembodiments.

In the drawings, specific arrangements or orderings of schematicelements, such as those representing devices, modules, instructionblocks and data elements, are shown for ease of description. However, itshould be understood by those skilled in the art that the specificordering or arrangement of the schematic elements in the drawings is notmeant to imply that a particular order or sequence of processing, orseparation of processes, is required. Further, the inclusion of aschematic element in a drawing is not meant to imply that such elementis required in all embodiments or that the features represented by suchelement may not be included in or combined with other elements in someembodiments.

Further, in the drawings, where connecting elements, such as solid ordashed lines or arrows, are used to illustrate a connection,relationship, or association between or among two or more otherschematic elements, the absence of any such connecting elements is notmeant to imply that no connection, relationship, or association canexist. In other words, some connections, relationships, or associationsbetween elements are not shown in the drawings so as not to obscure thedisclosure. In addition, for ease of illustration, a single connectingelement is used to represent multiple connections, relationships orassociations between elements. For example, where a connecting elementrepresents a communication of signals, data, or instructions, it shouldbe understood by those skilled in the art that such element representsone or multiple signal paths (e.g., a bus), as may be needed, to affectthe communication.

Reference will now be made in detail to embodiments, examples of whichare illustrated in the accompanying drawings. In the following detaileddescription, numerous specific details are set forth in order to providea thorough understanding of the various described embodiments. However,it will be apparent to one of ordinary skill in the art that the variousdescribed embodiments may be practiced without these specific details.In other instances, well-known methods, procedures, components,circuits, and networks have not been described in detail so as not tounnecessarily obscure aspects of the embodiments.

Several features are described hereafter that can each be usedindependently of one another or with any combination of other features.However, any individual feature may not address any of the problemsdiscussed above or might only address one of the problems discussedabove. Some of the problems discussed above might not be fully addressedby any of the features described herein. Although headings are provided,information related to a particular heading, but not found in thesection having that heading, may also be found elsewhere in thisdescription. Embodiments are described herein according to the followingoutline:

1. General Overview

2. Hardware Overview

3. Autonomous Vehicle Architecture

4. Autonomous Vehicle Inputs

5. Autonomous Vehicle Planning

6. Autonomous Vehicle Control

7. Computing System for Object Detection Using Pillars

8. Example Point Clouds and Pillars

9. Example Process for Detecting Objects and Operating the Vehicle Basedon the Detection of the Objects

General Overview

Autonomous vehicles driving in complex environments (e.g., an urbanenvironment) pose a great technological challenge. In order forautonomous vehicles to navigate these environments, the vehicles detectvarious types of objects such as vehicles, pedestrians, and bikes inreal-time using sensors such as LIDAR or RADAR. When an autonomousvehicle encounters a multi-way stop intersection, the autonomous vehicleuses sensors to detect other vehicles at the intersection, and determinewhen it is safe for the autonomous vehicle to proceed into theintersection. In some circumstances, other vehicles at the multi-waystop intersection may move toward the intersection when they do notintend to proceed through the intersection until after one or more othervehicles (e.g., another vehicle may slowly crawl forward when they arenext to have the right-of-way through the intersection to signal theirintent). In other circumstances, another vehicle may proceed into theintersection when they do not have the right-of-way according to localtraffic regulations (e.g., another vehicle may not notice that theautonomous vehicle arrived earlier at the intersection). The disclosedembodiments include a system and techniques that allow an autonomousvehicle to navigate a multi-way stop intersection in these and othercircumstances.

In particular, the system and techniques described herein allow anautonomous vehicle to navigate a multi-way stop intersection bydetermining whether the autonomous vehicle is clear to safely merge intoa travel lane (e.g., a lane of the roadway) corresponding to (e.g.,overlapping, nearest to) a planned travel path of the autonomousvehicle. By using safe merging techniques at a multi-way stopintersection, the autonomous vehicle can join the travel lane at a safedistance behind another vehicle traveling along the same path, withoutblocking paths of other vehicles. In some embodiments, the mergingtechniques described herein for multi-way stop intersections are thesame or similar merging techniques used when changing lanes or mergingon a multi-lane roadway.

Furthermore, in some embodiments, the system and techniques describedherein allow an autonomous vehicle to signal its intent to othervehicles at the multi-way stop intersection by proceeding into theintersection before another vehicle has fully exited the intersection.This early movement of the autonomous vehicle indicates to othervehicles that the autonomous vehicle is next to have the right-of-way atthe intersection, and may prevent other vehicles from proceedingout-of-turn.

Hardware Overview

FIG. 1 shows an example of an autonomous vehicle 100 having autonomouscapability.

As used herein, the term “autonomous capability” refers to a function,feature, or facility that enables a vehicle to be partially or fullyoperated without real-time human intervention, including withoutlimitation fully autonomous vehicles, highly autonomous vehicles, andconditionally autonomous vehicles.

As used herein, an autonomous vehicle (AV) is a vehicle that possessesautonomous capability.

As used herein, “vehicle” includes means of transportation of goods orpeople. For example, cars, buses, trains, airplanes, drones, trucks,boats, ships, submersibles, dirigibles, etc. A driverless car is anexample of a vehicle.

As used herein, “trajectory” refers to a path or route to navigate an AVfrom a first spatiotemporal location to second spatiotemporal location.In an embodiment, the first spatiotemporal location is referred to asthe initial or starting location and the second spatiotemporal locationis referred to as the destination, final location, goal, goal position,or goal location. In some examples, a trajectory is made up of one ormore segments (e.g., sections of road) and each segment is made up ofone or more blocks (e.g., portions of a lane or intersection). In anembodiment, the spatiotemporal locations correspond to real worldlocations. For example, the spatiotemporal locations are pick up ordrop-off locations to pick up or drop-off persons or goods.

As used herein, “sensor(s)” includes one or more hardware componentsthat detect information about the environment surrounding the sensor.Some of the hardware components can include sensing components (e.g.,image sensors, biometric sensors), transmitting and/or receivingcomponents (e.g., laser or radio frequency wave transmitters andreceivers), electronic components such as analog-to-digital converters,a data storage device (such as a RAM and/or a nonvolatile storage),software or firmware components and data processing components such asan ASIC (application-specific integrated circuit), a microprocessorand/or a microcontroller.

As used herein, a “scene description” is a data structure (e.g., list)or data stream that includes one or more classified or labeled objectsdetected by one or more sensors on the AV vehicle or provided by asource external to the AV.

As used herein, a “road” is a physical area that can be traversed by avehicle, and may correspond to a named thoroughfare (e.g., city street,interstate freeway, etc.) or may correspond to an unnamed thoroughfare(e.g., a driveway in a house or office building, a section of a parkinglot, a section of a vacant lot, a dirt path in a rural area, etc.).Because some vehicles (e.g., 4-wheel-drive pickup trucks, sport utilityvehicles, etc.) are capable of traversing a variety of physical areasnot specifically adapted for vehicle travel, a “road” may be a physicalarea not formally defined as a thoroughfare by any municipality or othergovernmental or administrative body.

As used herein, a “lane” is a portion of a road that can be traversed bya vehicle, and may correspond to most or all of the space between lanemarkings, or may correspond to only some (e.g., less than 50%) of thespace between lane markings. For example, a road having lane markingsspaced far apart might accommodate two or more vehicles between themarkings, such that one vehicle can pass the other without traversingthe lane markings, and thus could be interpreted as having a lanenarrower than the space between the lane markings, or having two lanesbetween the lane markings. A lane could also be interpreted in theabsence of lane markings. For example, a lane may be defined based onphysical features of an environment, e.g., rocks and trees along athoroughfare in a rural area.

“One or more” includes a function being performed by one element, afunction being performed by more than one element, e.g., in adistributed fashion, several functions being performed by one element,several functions being performed by several elements, or anycombination of the above.

It will also be understood that, although the terms first, second, etc.are, in some instances, used herein to describe various elements, theseelements should not be limited by these terms. These terms are only usedto distinguish one element from another. For example, a first contactcould be termed a second contact, and, similarly, a second contact couldbe termed a first contact, without departing from the scope of thevarious described embodiments. The first contact and the second contactare both contacts, but they are not the same contact, unless specifiedotherwise.

The terminology used in the description of the various describedembodiments herein is for the purpose of describing particularembodiments only and is not intended to be limiting. As used in thedescription of the various described embodiments and the appendedclaims, the singular forms “a,” “an” and “the” are intended to includethe plural forms as well, unless the context clearly indicatesotherwise. It will also be understood that the term “and/or” as usedherein refers to and encompasses any and all possible combinations ofone or more of the associated listed items. It will be furtherunderstood that the terms “includes,” “including,” “comprises,” and/or“comprising,” when used in this description, specify the presence ofstated features, integers, steps, operations, elements, and/orcomponents, but do not preclude the presence or addition of one or moreother features, integers, steps, operations, elements, components,and/or groups thereof.

As used herein, the term “if” is, optionally, construed to mean “when”or “upon” or “in response to determining” or “in response to detecting,”depending on the context. Similarly, the phrase “if it is determined” or“if [a stated condition or event] is detected” is, optionally, construedto mean “upon determining” or “in response to determining” or “upondetecting [the stated condition or event]” or “in response to detecting[the stated condition or event],” depending on the context.

As used herein, an AV system refers to the AV along with the array ofhardware, software, stored data, and data generated in real-time thatsupports the operation of the AV. In an embodiment, the AV system isincorporated within the AV. In an embodiment, the AV system is spreadacross several locations. For example, some of the software of the AVsystem is implemented on a cloud computing environment similar to cloudcomputing environment 200 described below with respect to FIG. 2.

In general, this document describes technologies applicable to anyvehicles that have one or more autonomous capabilities including fullyautonomous vehicles, highly autonomous vehicles, and conditionallyautonomous vehicles, such as so-called Level 5, Level 4 and Level 3vehicles, respectively (see SAE International's standard J3016: Taxonomyand Definitions for Terms Related to On-Road Motor Vehicle AutomatedDriving Systems, which is incorporated by reference in its entirety, formore details on the classification of levels of autonomy in vehicles).The technologies described in this document are also applicable topartially autonomous vehicles and driver assisted vehicles, such asso-called Level 2 and Level 1 vehicles (see SAE International's standardJ3016: Taxonomy and Definitions for Terms Related to On-Road MotorVehicle Automated Driving Systems). In an embodiment, one or more of theLevel 1, 2, 3, 4 and 5 vehicle systems may automate certain vehicleoperations (e.g., steering, braking, and using maps) under certainoperating conditions based on processing of sensor inputs. Thetechnologies described in this document can benefit vehicles in anylevels, ranging from fully autonomous vehicles to human-operatedvehicles.

Referring to FIG. 1, an AV system 120 operates the AV 100 along atrajectory 198 through an environment 190 to a destination 199(sometimes referred to as a final location) while avoiding objects(e.g., natural obstructions 191, vehicles 193, pedestrians 192,cyclists, and other obstacles) and obeying rules of the road (e.g.,rules of operation or driving preferences).

In an embodiment, the AV system 120 includes devices 101 that areinstrumented to receive and act on operational commands from thecomputer processors 146. In an embodiment, computing processors 146 aresimilar to the processor 304 described below in reference to FIG. 3.Examples of devices 101 include a steering control 102, brakes 103,gears, accelerator pedal or other acceleration control mechanisms,windshield wipers, side-door locks, window controls, andturn-indicators.

In an embodiment, the AV system 120 includes sensors 121 for measuringor inferring properties of state or condition of the AV 100, such as theAV's position, linear and angular velocity and acceleration, and heading(e.g., an orientation of the leading end of AV 100). Example of sensors121 are GPS, inertial measurement units (IMU) that measure both vehiclelinear accelerations and angular rates, wheel speed sensors formeasuring or estimating wheel slip ratios, wheel brake pressure orbraking torque sensors, engine torque or wheel torque sensors, andsteering angle and angular rate sensors.

In an embodiment, the sensors 121 also include sensors for sensing ormeasuring properties of the AV's environment. For example, monocular orstereo video cameras 122 in the visible light, infrared or thermal (orboth) spectra, LiDAR 123, RADAR, ultrasonic sensors, time-of-flight(TOF) depth sensors, speed sensors, temperature sensors, humiditysensors, and precipitation sensors.

In an embodiment, the AV system 120 includes a data storage unit 142 andmemory 144 for storing machine instructions associated with computerprocessors 146 or data collected by sensors 121. In an embodiment, thedata storage unit 142 is similar to the ROM 308 or storage device 310described below in relation to FIG. 3. In an embodiment, memory 144 issimilar to the main memory 306 described below. In an embodiment, thedata storage unit 142 and memory 144 store historical, real-time, and/orpredictive information about the environment 190. In an embodiment, thestored information includes maps, driving performance, trafficcongestion updates or weather conditions. In an embodiment, datarelating to the environment 190 is transmitted to the AV 100 via acommunications channel from a remotely located database 134.

In an embodiment, the AV system 120 includes communications devices 140for communicating measured or inferred properties of other vehicles'states and conditions, such as positions, linear and angular velocities,linear and angular accelerations, and linear and angular headings to theAV 100. These devices include Vehicle-to-Vehicle (V2V) andVehicle-to-Infrastructure (V2I) communication devices and devices forwireless communications over point-to-point or ad hoc networks or both.In an embodiment, the communications devices 140 communicate across theelectromagnetic spectrum (including radio and optical communications) orother media (e.g., air and acoustic media). A combination ofVehicle-to-Vehicle (V2V) Vehicle-to-Infrastructure (V2I) communication(and, in some embodiments, one or more other types of communication) issometimes referred to as Vehicle-to-Everything (V2X) communication. V2Xcommunication typically conforms to one or more communications standardsfor communication with, between, and among autonomous vehicles.

In an embodiment, the communication devices 140 include communicationinterfaces. For example, wired, wireless, WiMAX, WiFi, Bluetooth,satellite, cellular, optical, near field, infrared, or radio interfaces.The communication interfaces transmit data from a remotely locateddatabase 134 to AV system 120. In an embodiment, the remotely locateddatabase 134 is embedded in a cloud computing environment 200 asdescribed in FIG. 2. The communication interfaces 140 transmit datacollected from sensors 121 or other data related to the operation of AV100 to the remotely located database 134. In an embodiment,communication interfaces 140 transmit information that relates toteleoperations to the AV 100. In some embodiments, the AV 100communicates with other remote (e.g., “cloud”) servers 136.

In an embodiment, the remotely located database 134 also stores andtransmits digital data (e.g., storing data such as road and streetlocations). Such data is stored on the memory 144 on the AV 100, ortransmitted to the AV 100 via a communications channel from the remotelylocated database 134.

In an embodiment, the remotely located database 134 stores and transmitshistorical information about driving properties (e.g., speed andacceleration profiles) of vehicles that have previously traveled alongtrajectory 198 at similar times of day. In one implementation, such datamay be stored on the memory 144 on the AV 100, or transmitted to the AV100 via a communications channel from the remotely located database 134.

Computing devices 146 located on the AV 100 algorithmically generatecontrol actions based on both real-time sensor data and priorinformation, allowing the AV system 120 to execute its autonomousdriving capabilities.

In an embodiment, the AV system 120 includes computer peripherals 132coupled to computing devices 146 for providing information and alertsto, and receiving input from, a user (e.g., an occupant or a remoteuser) of the AV 100. In an embodiment, peripherals 132 are similar tothe display 312, input device 314, and cursor controller 316 discussedbelow in reference to FIG. 3. The coupling is wireless or wired. Any twoor more of the interface devices may be integrated into a single device.

FIG. 2 illustrates an example “cloud” computing environment. Cloudcomputing is a model of service delivery for enabling convenient,on-demand network access to a shared pool of configurable computingresources (e.g., networks, network bandwidth, servers, processing,memory, storage, applications, virtual machines, and services). Intypical cloud computing systems, one or more large cloud data centershouse the machines used to deliver the services provided by the cloud.Referring now to FIG. 2, the cloud computing environment 200 includescloud data centers 204 a, 204 b, and 204 c that are interconnectedthrough the cloud 202. Data centers 204 a, 204 b, and 204 c providecloud computing services to computer systems 206 a, 206 b, 206 c, 206 d,206 e, and 206 f connected to cloud 202.

The cloud computing environment 200 includes one or more cloud datacenters. In general, a cloud data center, for example the cloud datacenter 204 a shown in FIG. 2, refers to the physical arrangement ofservers that make up a cloud, for example the cloud 202 shown in FIG. 2,or a particular portion of a cloud. For example, servers are physicallyarranged in the cloud datacenter into rooms, groups, rows, and racks. Acloud datacenter has one or more zones, which include one or more roomsof servers. Each room has one or more rows of servers, and each rowincludes one or more racks. Each rack includes one or more individualserver nodes. In some implementation, servers in zones, rooms, racks,and/or rows are arranged into groups based on physical infrastructurerequirements of the datacenter facility, which include power, energy,thermal, heat, and/or other requirements. In an embodiment, the servernodes are similar to the computer system described in FIG. 3. The datacenter 204 a has many computing systems distributed through many racks.

The cloud 202 includes cloud data centers 204 a, 204 b, and 204 c alongwith the network and networking resources (for example, networkingequipment, nodes, routers, switches, and networking cables) thatinterconnect the cloud data centers 204 a, 204 b, and 204 c and helpfacilitate the computing systems' 206 a-f access to cloud computingservices. In an embodiment, the network represents any combination ofone or more local networks, wide area networks, or internetworks coupledusing wired or wireless links deployed using terrestrial or satelliteconnections. Data exchanged over the network, is transferred using anynumber of network layer protocols, such as Internet Protocol (IP),Multiprotocol Label Switching (MPLS), Asynchronous Transfer Mode (ATM),Frame Relay, etc. Furthermore, in embodiments where the networkrepresents a combination of multiple sub-networks, different networklayer protocols are used at each of the underlying sub-networks. In someembodiments, the network represents one or more interconnectedinternetworks, such as the public Internet.

The computing systems 206 a-f or cloud computing services consumers areconnected to the cloud 202 through network links and network adapters.In an embodiment, the computing systems 206 a-f are implemented asvarious computing devices, for example servers, desktops, laptops,tablet, smartphones, Internet of Things (IoT) devices, autonomousvehicles (including, cars, drones, shuttles, trains, buses, etc.) andconsumer electronics. In an embodiment, the computing systems 206 a-fare implemented in or as a part of other systems.

FIG. 3 illustrates a computer system 300. In an implementation, thecomputer system 300 is a special purpose computing device. Thespecial-purpose computing device is hard-wired to perform the techniquesor includes digital electronic devices such as one or moreapplication-specific integrated circuits (ASICs) or field programmablegate arrays (FPGAs) that are persistently programmed to perform thetechniques, or may include one or more general purpose hardwareprocessors programmed to perform the techniques pursuant to programinstructions in firmware, memory, other storage, or a combination. Suchspecial-purpose computing devices may also combine custom hard-wiredlogic, ASICs, or FPGAs with custom programming to accomplish thetechniques. In various embodiments, the special-purpose computingdevices are desktop computer systems, portable computer systems,handheld devices, network devices or any other device that incorporateshard-wired and/or program logic to implement the techniques.

In an embodiment, the computer system 300 includes a bus 302 or othercommunication mechanism for communicating information, and a hardwareprocessor 304 coupled with a bus 302 for processing information. Thehardware processor 304 is, for example, a general-purposemicroprocessor. The computer system 300 also includes a main memory 306,such as a random-access memory (RAM) or other dynamic storage device,coupled to the bus 302 for storing information and instructions to beexecuted by processor 304. In one implementation, the main memory 306 isused for storing temporary variables or other intermediate informationduring execution of instructions to be executed by the processor 304.Such instructions, when stored in non-transitory storage mediaaccessible to the processor 304, render the computer system 300 into aspecial-purpose machine that is customized to perform the operationsspecified in the instructions.

In an embodiment, the computer system 300 further includes a read onlymemory (ROM) 308 or other static storage device coupled to the bus 302for storing static information and instructions for the processor 304. Astorage device 310, such as a magnetic disk, optical disk, solid-statedrive, or three-dimensional cross point memory is provided and coupledto the bus 302 for storing information and instructions.

In an embodiment, the computer system 300 is coupled via the bus 302 toa display 312, such as a cathode ray tube (CRT), a liquid crystaldisplay (LCD), plasma display, light emitting diode (LED) display, or anorganic light emitting diode (OLED) display for displaying informationto a computer user. An input device 314, including alphanumeric andother keys, is coupled to bus 302 for communicating information andcommand selections to the processor 304. Another type of user inputdevice is a cursor controller 316, such as a mouse, a trackball, atouch-enabled display, or cursor direction keys for communicatingdirection information and command selections to the processor 304 andfor controlling cursor movement on the display 312. This input devicetypically has two degrees of freedom in two axes, a first axis (e.g.,x-axis) and a second axis (e.g., y-axis), that allows the device tospecify positions in a plane.

According to one embodiment, the techniques herein are performed by thecomputer system 300 in response to the processor 304 executing one ormore sequences of one or more instructions contained in the main memory306. Such instructions are read into the main memory 306 from anotherstorage medium, such as the storage device 310. Execution of thesequences of instructions contained in the main memory 306 causes theprocessor 304 to perform the process steps described herein. Inalternative embodiments, hard-wired circuitry is used in place of or incombination with software instructions.

The term “storage media” as used herein refers to any non-transitorymedia that store data and/or instructions that cause a machine tooperate in a specific fashion. Such storage media includes non-volatilemedia and/or volatile media. Non-volatile media includes, for example,optical disks, magnetic disks, solid-state drives, or three-dimensionalcross point memory, such as the storage device 310. Volatile mediaincludes dynamic memory, such as the main memory 306. Common forms ofstorage media include, for example, a floppy disk, a flexible disk, harddisk, solid-state drive, magnetic tape, or any other magnetic datastorage medium, a CD-ROM, any other optical data storage medium, anyphysical medium with patterns of holes, a RAM, a PROM, and EPROM, aFLASH-EPROM, NV-RAM, or any other memory chip or cartridge.

Storage media is distinct from but may be used in conjunction withtransmission media. Transmission media participates in transferringinformation between storage media. For example, transmission mediaincludes coaxial cables, copper wire and fiber optics, including thewires that comprise the bus 302. Transmission media can also take theform of acoustic or light waves, such as those generated duringradio-wave and infrared data communications.

In an embodiment, various forms of media are involved in carrying one ormore sequences of one or more instructions to the processor 304 forexecution. For example, the instructions are initially carried on amagnetic disk or solid-state drive of a remote computer. The remotecomputer loads the instructions into its dynamic memory and send theinstructions over a telephone line using a modem. A modem local to thecomputer system 300 receives the data on the telephone line and use aninfrared transmitter to convert the data to an infrared signal. Aninfrared detector receives the data carried in the infrared signal andappropriate circuitry places the data on the bus 302. The bus 302carries the data to the main memory 306, from which processor 304retrieves and executes the instructions. The instructions received bythe main memory 306 may optionally be stored on the storage device 310either before or after execution by processor 304.

The computer system 300 also includes a communication interface 318coupled to the bus 302. The communication interface 318 provides atwo-way data communication coupling to a network link 320 that isconnected to a local network 322. For example, the communicationinterface 318 is an integrated service digital network (ISDN) card,cable modem, satellite modem, or a modem to provide a data communicationconnection to a corresponding type of telephone line. As anotherexample, the communication interface 318 is a local area network (LAN)card to provide a data communication connection to a compatible LAN. Insome implementations, wireless links are also implemented. In any suchimplementation, the communication interface 318 sends and receiveselectrical, electromagnetic, or optical signals that carry digital datastreams representing various types of information.

The network link 320 typically provides data communication through oneor more networks to other data devices. For example, the network link320 provides a connection through the local network 322 to a hostcomputer 324 or to a cloud data center or equipment operated by anInternet Service Provider (ISP) 326. The ISP 326 in turn provides datacommunication services through the world-wide packet data communicationnetwork now commonly referred to as the “Internet” 328. The localnetwork 322 and Internet 328 both use electrical, electromagnetic oroptical signals that carry digital data streams. The signals through thevarious networks and the signals on the network link 320 and through thecommunication interface 318, which carry the digital data to and fromthe computer system 300, are example forms of transmission media. In anembodiment, the network 320 contains the cloud 202 or a part of thecloud 202 described above.

The computer system 300 sends messages and receives data, includingprogram code, through the network(s), the network link 320, and thecommunication interface 318. In an embodiment, the computer system 300receives code for processing. The received code is executed by theprocessor 304 as it is received, and/or stored in storage device 310, orother non-volatile storage for later execution.

Autonomous Vehicle Architecture

FIG. 4 shows an example architecture 400 for an autonomous vehicle(e.g., the AV 100 shown in FIG. 1). The architecture 400 includes aperception module 402 (sometimes referred to as a perception circuit), aplanning module 404 (sometimes referred to as a planning circuit), acontrol module 406 (sometimes referred to as a control circuit), alocalization module 408 (sometimes referred to as a localizationcircuit), and a database module 410 (sometimes referred to as a databasecircuit). Each module plays a role in the operation of the AV 100.Together, the modules 402, 404, 406, 408, and 410 may be part of the AVsystem 120 shown in FIG. 1. In some embodiments, any of the modules 402,404, 406, 408, and 410 is a combination of computer software (e.g.,executable code stored on a computer-readable medium) and computerhardware (e.g., one or more microprocessors, microcontrollers,application-specific integrated circuits [ASICs]), hardware memorydevices, other types of integrated circuits, other types of computerhardware, or a combination of any or all of these things).

In use, the planning module 404 receives data representing a destination412 and determines data representing a trajectory 414 (sometimesreferred to as a route) that can be traveled by the AV 100 to reach(e.g., arrive at) the destination 412. In order for the planning module404 to determine the data representing the trajectory 414, the planningmodule 404 receives data from the perception module 402, thelocalization module 408, and the database module 410.

The perception module 402 identifies nearby physical objects using oneor more sensors 121, e.g., as also shown in FIG. 1. The objects areclassified (e.g., grouped into types such as pedestrian, bicycle,automobile, traffic sign, etc.) and a scene description including theclassified objects 416 is provided to the planning module 404.

The planning module 404 also receives data representing the AV position418 from the localization module 408. The localization module 408determines the AV position by using data from the sensors 121 and datafrom the database module 410 (e.g., a geographic data) to calculate aposition. For example, the localization module 408 uses data from a GNSS(Global Navigation Satellite System) sensor and geographic data tocalculate a longitude and latitude of the AV. In an embodiment, dataused by the localization module 408 includes high-precision maps of theroadway geometric properties, maps describing road network connectivityproperties, maps describing roadway physical properties (such as trafficspeed, traffic volume, the number of vehicular and cyclist trafficlanes, lane width, lane traffic directions, or lane marker types andlocations, or combinations of them), and maps describing the spatiallocations of road features such as crosswalks, traffic signs or othertravel signals of various types.

The control module 406 receives the data representing the trajectory 414and the data representing the AV position 418 and operates the controlfunctions 420 a-c (e.g., steering, throttling, braking, ignition) of theAV in a manner that will cause the AV 100 to travel the trajectory 414to the destination 412. For example, if the trajectory 414 includes aleft turn, the control module 406 will operate the control functions 420a-c in a manner such that the steering angle of the steering functionwill cause the AV 100 to turn left and the throttling and braking willcause the AV 100 to pause and wait for passing pedestrians or vehiclesbefore the turn is made.

Autonomous Vehicle Inputs

FIG. 5 shows an example of inputs 502 a-d (e.g., sensors 121 shown inFIG. 1) and outputs 504 a-d (e.g., sensor data) that is used by theperception module 402 (FIG. 4). One input 502 a is a LiDAR (LightDetection and Ranging) system (e.g., LiDAR 123 shown in FIG. 1). LiDARis a technology that uses light (e.g., bursts of light such as infraredlight) to obtain data about physical objects in its line of sight. ALiDAR system produces LiDAR data as output 504 a. For example, LiDARdata is collections of 3D or 2D points (also known as a point clouds)that are used to construct a representation of the environment 190.

Another input 502 b is a RADAR system. RADAR is a technology that usesradio waves to obtain data about nearby physical objects. RADARs canobtain data about objects not within the line of sight of a LiDARsystem. A RADAR system 502 b produces RADAR data as output 504 b. Forexample, RADAR data are one or more radio frequency electromagneticsignals that are used to construct a representation of the environment190.

Another input 502 c is a camera system. A camera system uses one or morecameras (e.g., digital cameras using a light sensor such as acharge-coupled device [CCD]) to obtain information about nearby physicalobjects. A camera system produces camera data as output 504 c. Cameradata often takes the form of image data (e.g., data in an image dataformat such as RAW, JPEG, PNG, etc.). In some examples, the camerasystem has multiple independent cameras, e.g., for the purpose ofstereopsis (stereo vision), which enables the camera system to perceivedepth. Although the objects perceived by the camera system are describedhere as “nearby,” this is relative to the AV. In use, the camera systemmay be configured to “see” objects far, e.g., up to a kilometer or moreahead of the AV. Accordingly, the camera system may have features suchas sensors and lenses that are optimized for perceiving objects that arefar away.

Another input 502 d is a traffic light detection (TLD) system. A TLDsystem uses one or more cameras to obtain information about trafficlights, street signs, and other physical objects that provide visualnavigation information. A TLD system produces TLD data as output 504 d.TLD data often takes the form of image data (e.g., data in an image dataformat such as RAW, JPEG, PNG, etc.). A TLD system differs from a systemincorporating a camera in that a TLD system uses a camera with a widefield of view (e.g., using a wide-angle lens or a fish-eye lens) inorder to obtain information about as many physical objects providingvisual navigation information as possible, so that the AV 100 has accessto all relevant navigation information provided by these objects. Forexample, the viewing angle of the TLD system may be about 120 degrees ormore.

In some embodiments, outputs 504 a-d are combined using a sensor fusiontechnique. Thus, either the individual outputs 504 a-d are provided toother systems of the AV 100 (e.g., provided to a planning module 404 asshown in FIG. 4), or the combined output can be provided to the othersystems, either in the form of a single combined output or multiplecombined outputs of the same type (e.g., using the same combinationtechnique or combining the same outputs or both) or different types type(e.g., using different respective combination techniques or combiningdifferent respective outputs or both). In some embodiments, an earlyfusion technique is used. An early fusion technique is characterized bycombining outputs before one or more data processing steps are appliedto the combined output. In some embodiments, a late fusion technique isused. A late fusion technique is characterized by combining outputsafter one or more data processing steps are applied to the individualoutputs.

FIG. 6 shows an example of a LiDAR system 602 (e.g., the input 502 ashown in FIG. 5). The LiDAR system 602 emits light 604 a-c from a lightemitter 606 (e.g., a laser transmitter). Light emitted by a LiDAR systemis typically not in the visible spectrum; for example, infrared light isoften used. Some of the light 604 b emitted encounters a physical object608 (e.g., a vehicle) and reflects back to the LiDAR system 602. (Lightemitted from a LiDAR system typically does not penetrate physicalobjects, e.g., physical objects in solid form.) The LiDAR system 602also has one or more light detectors 610, which detect the reflectedlight. In an embodiment, one or more data processing systems associatedwith the LiDAR system generates an image 612 representing the field ofview 614 of the LiDAR system. The image 612 includes information thatrepresents the boundaries 616 of a physical object 608. In this way, theimage 612 is used to determine the boundaries 616 of one or morephysical objects near an AV.

FIG. 7 shows the LiDAR system 602 in operation. In the scenario shown inthis figure, the AV 100 receives both camera system output 504 c in theform of an image 702 and LiDAR system output 504 a in the form of LiDARdata points 704. In use, the data processing systems of the AV 100compares the image 702 to the data points 704. In particular, a physicalobject 706 identified in the image 702 is also identified among the datapoints 704. In this way, the AV 100 perceives the boundaries of thephysical object based on the contour and density of the data points 704.

FIG. 8 shows the operation of the LiDAR system 602 in additional detail.As described above, the AV 100 detects the boundary of a physical objectbased on characteristics of the data points detected by the LiDAR system602. As shown in FIG. 8, a flat object, such as the ground 802, willreflect light 804 a-d emitted from a LiDAR system 602 in a consistentmanner. Put another way, because the LiDAR system 602 emits light usingconsistent spacing, the ground 802 will reflect light back to the LiDARsystem 602 with the same consistent spacing. As the AV 100 travels overthe ground 802, the LiDAR system 602 will continue to detect lightreflected by the next valid ground point 806 if nothing is obstructingthe road. However, if an object 808 obstructs the road, light 804 e-femitted by the LiDAR system 602 will be reflected from points 810 a-b ina manner inconsistent with the expected consistent manner. From thisinformation, the AV 100 can determine that the object 808 is present.

Path Planning

FIG. 9 shows a block diagram 900 of the relationships between inputs andoutputs of a planning module 404 (e.g., as shown in FIG. 4). In general,the output of a planning module 404 is a route 902 from a start point904 (e.g., source location or initial location), and an end point 906(e.g., destination or final location). The route 902 is typicallydefined by one or more segments. For example, a segment is a distance tobe traveled over at least a portion of a street, road, highway,driveway, or other physical area appropriate for automobile travel. Insome examples, e.g., if the AV 100 is an off-road capable vehicle suchas a four-wheel-drive (4WD) or all-wheel-drive (AWD) car, SUV, pick-uptruck, or the like, the route 902 includes “off-road” segments such asunpaved paths or open fields.

In addition to the route 902, a planning module also outputs lane-levelroute planning data 908. The lane-level route planning data 908 is usedto traverse segments of the route 902 based on conditions of the segmentat a particular time. For example, if the route 902 includes amulti-lane highway, the lane-level route planning data 908 includestrajectory planning data 910 that the AV 100 can use to choose a laneamong the multiple lanes, e.g., based on whether an exit is approaching,whether one or more of the lanes have other vehicles, or other factorsthat vary over the course of a few minutes or less. Similarly, in someimplementations, the lane-level route planning data 908 includes speedconstraints 912 specific to a segment of the route 902. For example, ifthe segment includes pedestrians or un-expected traffic, the speedconstraints 912 may limit the AV 100 to a travel speed slower than anexpected speed, e.g., a speed based on speed limit data for the segment.

In an embodiment, the inputs to the planning module 404 includesdatabase data 914 (e.g., from the database module 410 shown in FIG. 4),current location data 916 (e.g., the AV position 418 shown in FIG. 4),destination data 918 (e.g., for the destination 412 shown in FIG. 4),and object data 920 (e.g., the classified objects 416 as perceived bythe perception module 402 as shown in FIG. 4). In some embodiments, thedatabase data 914 includes rules used in planning. Rules are specifiedusing a formal language, e.g., using Boolean logic. In any givensituation encountered by the AV 100, at least some of the rules willapply to the situation. A rule applies to a given situation if the rulehas conditions that are met based on information available to the AV100, e.g., information about the surrounding environment. Rules can havepriority. For example, a rule that says, “if the road is a freeway, moveto the leftmost lane” can have a lower priority than “if the exit isapproaching within a mile, move to the rightmost lane.”

FIG. 10 shows a directed graph 1000 used in path planning, e.g., by theplanning module 404 (FIG. 4). In general, a directed graph 1000 like theone shown in FIG. 10 is used to determine a path between any start point1002 and end point 1004. In real-world terms, the distance separatingthe start point 1002 and end point 1004 may be relatively large (e.g, intwo different metropolitan areas) or may be relatively small (e.g., twointersections abutting a city block or two lanes of a multi-lane road).

In an embodiment, the directed graph 1000 has nodes 1006 a-drepresenting different locations between the start point 1002 and theend point 1004 that could be occupied by an AV 100. In some examples,e.g., when the start point 1002 and end point 1004 represent differentmetropolitan areas, the nodes 1006 a-d represent segments of roads. Insome examples, e.g., when the start point 1002 and the end point 1004represent different locations on the same road, the nodes 1006 a-drepresent different positions on that road. In this way, the directedgraph 1000 includes information at varying levels of granularity. In anembodiment, a directed graph having high granularity is also a subgraphof another directed graph having a larger scale. For example, a directedgraph in which the start point 1002 and the end point 1004 are far away(e.g., many miles apart) has most of its information at a lowgranularity and is based on stored data, but also includes some highgranularity information for the portion of the graph that representsphysical locations in the field of view of the AV 100.

The nodes 1006 a-d are distinct from objects 1008 a-b which cannotoverlap with a node. In an embodiment, when granularity is low, theobjects 1008 a-b represent regions that cannot be traversed byautomobile, e.g., areas that have no streets or roads. When granularityis high, the objects 1008 a-b represent physical objects in the field ofview of the AV 100, e.g., other automobiles, pedestrians, or otherentities with which the AV 100 cannot share physical space. In anembodiment, some or all of the objects 1008 a-b are a static objects(e.g., an object that does not change position such as a street lamp orutility pole) or dynamic objects (e.g., an object that is capable ofchanging position such as a pedestrian or other car).

The nodes 1006 a-d are connected by edges 1010 a-c. If two nodes 1006a-b are connected by an edge 1010 a, it is possible for an AV 100 totravel between one node 1006 a and the other node 1006 b, e.g., withouthaving to travel to an intermediate node before arriving at the othernode 1006 b. (When we refer to an AV 100 traveling between nodes, wemean that the AV 100 travels between the two physical positionsrepresented by the respective nodes.) The edges 1010 a-c are oftenbidirectional, in the sense that an AV 100 travels from a first node toa second node, or from the second node to the first node. In anembodiment, edges 1010 a-c are unidirectional, in the sense that an AV100 can travel from a first node to a second node, however the AV 100cannot travel from the second node to the first node. Edges 1010 a-c areunidirectional when they represent, for example, one-way streets,individual lanes of a street, road, or highway, or other features thatcan only be traversed in one direction due to legal or physicalconstraints.

In an embodiment, the planning module 404 uses the directed graph 1000to identify a path 1012 made up of nodes and edges between the startpoint 1002 and end point 1004.

An edge 1010 a-c has an associated cost 1014 a-b. The cost 1014 a-b is avalue that represents the resources that will be expended if the AV 100chooses that edge. A typical resource is time. For example, if one edge1010 a represents a physical distance that is twice that as another edge1010 b, then the associated cost 1014 a of the first edge 1010 a may betwice the associated cost 1014 b of the second edge 1010 b. Otherfactors that affect time include expected traffic, number ofintersections, speed limit, etc. Another typical resource is fueleconomy. Two edges 1010 a-b may represent the same physical distance,but one edge 1010 a may require more fuel than another edge 1010b, e.g.,because of road conditions, expected weather, etc.

When the planning module 404 identifies a path 1012 between the startpoint 1002 and end point 1004, the planning module 404 typically choosesa path optimized for cost, e.g., the path that has the least total costwhen the individual costs of the edges are added together.

Autonomous Vehicle Control

FIG. 11 shows a block diagram 1100 of the inputs and outputs of acontrol module 406 (e.g., as shown in FIG. 4). A control module operatesin accordance with a controller 1102 which includes, for example, one ormore processors (e.g., one or more computer processors such asmicroprocessors or microcontrollers or both) similar to processor 304,short-term and/or long-term data storage (e.g., memory random-accessmemory or flash memory or both) similar to main memory 306, ROM 308, andstorage device 310, and instructions stored in memory that carry outoperations of the controller 1102 when the instructions are executed(e.g., by the one or more processors).

In an embodiment, the controller 1102 receives data representing adesired output 1104. The desired output 1104 typically includes avelocity, e.g., a speed and a heading. The desired output 1104 can bebased on, for example, data received from a planning module 404 (e.g.,as shown in FIG. 4). In accordance with the desired output 1104, thecontroller 1102 produces data usable as a throttle input 1106 and asteering input 1108. The throttle input 1106 represents the magnitude inwhich to engage the throttle (e.g., acceleration control) of an AV 100,e.g., by engaging the steering pedal, or engaging another throttlecontrol, to achieve the desired output 1104. In some examples, thethrottle input 1106 also includes data usable to engage the brake (e.g.,deceleration control) of the AV 100. The steering input 1108 representsa steering angle, e.g., the angle at which the steering control (e.g.,steering wheel, steering angle actuator, or other functionality forcontrolling steering angle) of the AV should be positioned to achievethe desired output 1104.

In an embodiment, the controller 1102 receives feedback that is used inadjusting the inputs provided to the throttle and steering. For example,if the AV 100 encounters a disturbance 1110, such as a hill, themeasured speed 1112 of the AV 100 is lowered below the desired outputspeed. In an embodiment, any measured output 1114 is provided to thecontroller 1102 so that the necessary adjustments are performed, e.g.,based on the differential 1113 between the measured speed and desiredoutput. The measured output 1114 includes measured position 1116,measured velocity 1118, (including speed and heading), measuredacceleration 1120, and other outputs measurable by sensors of the AV100.

In an embodiment, information about the disturbance 1110 is detected inadvance, e.g., by a sensor such as a camera or LiDAR sensor, andprovided to a predictive feedback module 1122. The predictive feedbackmodule 1122 then provides information to the controller 1102 that thecontroller 1102 can use to adjust accordingly. For example, if thesensors of the AV 100 detect (“see”) a hill, this information can beused by the controller 1102 to prepare to engage the throttle at theappropriate time to avoid significant deceleration.

FIG. 12 shows a block diagram 1200 of the inputs, outputs, andcomponents of the controller 1102. The controller 1102 has a speedprofiler 1202 which affects the operation of a throttle/brake controller1204. For example, the speed profiler 1202 instructs the throttle/brakecontroller 1204 to engage acceleration or engage deceleration using thethrottle/brake 1206 depending on, e.g., feedback received by thecontroller 1102 and processed by the speed profiler 1202.

The controller 1102 also has a lateral tracking controller 1208 whichaffects the operation of a steering controller 1210. For example, thelateral tracking controller 1208 instructs the steering controller 1210to adjust the position of the steering angle actuator 1212 depending on,e.g., feedback received by the controller 1102 and processed by thelateral tracking controller 1208.

The controller 1102 receives several inputs used to determine how tocontrol the throttle/brake 1206 and steering angle actuator 1212. Aplanning module 404 provides information used by the controller 1102,for example, to choose a heading when the AV 100 begins operation and todetermine which road segment to traverse when the AV 100 reaches anintersection. A localization module 408 provides information to thecontroller 1102 describing the current location of the AV 100, forexample, so that the controller 1102 can determine if the AV 100 is at alocation expected based on the manner in which the throttle/brake 1206and steering angle actuator 1212 are being controlled. In an embodiment,the controller 1102 receives information from other inputs 1214, e.g.,information received from databases, computer networks, etc.

Navigating Multi-way Stop Intersections

FIGS. 13A-13L illustrate examples of AV 100 navigating a multi-way stopintersection in environment 190. In particular, FIGS. 13A-13D illustrateAV 100 navigating a multi-way stop intersection when another vehicleturns right into the same lane as AV 100, FIGS. 13E-13H illustrate AV100 navigating a multi-way stop intersection when another vehicle turnsleft across the lane of AV 100, and FIGS. 13I-13L illustrate AV 100turning left at a multi-way stop intersection into the lane of anothervehicle.

As shown in FIG. 13A, AV 100 is stopped at a primary stopline 1308 ofthe intersection. The primary stopline 1308 is a real or virtual linewhere a vehicle is expected to stop at the intersection. For example,the primary stopline 1308 corresponds to the expected stopping positionas designated by stop sign 1304 and stop road marking 1306. Based ondestination of AV 100, AV system 120 determines a planned travel path1310 of AV 100 through the intersection (e.g., a path the AV 100 isexpected to take from the stopline 1308 to an exit of the intersectionbased on the destination of AV 100). The AV system 120 can alsodetermine a travel lane 1312 corresponding to (e.g., overlapping,nearest to) the planned travel path 1310. In some embodiments, thetravel lane 1312 corresponds to one or more lanes of the roadway wherethe AV 100 is planning to go.

As shown in FIG. 13A, two other vehicles 1302 a and 1302 b are also ator near the multi-way stop intersection. Based on local trafficregulations, vehicle 1302 a has the precedence at the intersection(e.g., vehicle 1302 a arrived at the intersection before vehicle 1302 band AV 100). When a vehicle has the highest precedence, it is expectedto proceed into the intersection before vehicles with lower precedences,based on the local traffic regulations (e.g., the highest precedencevehicle arrived at the intersection before other vehicles at theintersection; the highest precedence vehicle is on the right of anothervehicle that arrived at the intersection at approximately the same time;the highest precedence vehicle is going straight and another vehiclethat arrived at the intersection at approximately the same time isturning).

AV system 120 determines that vehicle 1302 a has the highest precedenceand determines an expected travel path 1314 of vehicle 1302 a. Ifvehicle 1302 a is stopped (or moving at less than a predetermined speed)and not indicating a turn with a turn signal, then AV system 120initially determines the expected travel path 1314 of vehicle 1302 awill be straight toward the intersection. As shown in FIG. 13A, expectedtravel path 1314 will cause vehicle 1302 a to intersect travel lane 1312of AV 100.

As shown in FIG. 13B, in response to the determination that the expectedtravel path 1314 of vehicle 1302 a will cause vehicle 1302 a tointersect travel lane 1312 of AV 100, the AV system 120 instructs AV 100to wait at the primary stopline 1308. AV 100 waits at the primarystopline 1308 until AV system 120 determines that the planned travelpath 1310 of AV 100 satisfies a set of one or more clearance criteria.The clearance criteria include a criterion that is satisfied when AV 100is clear to safely merge into the travel lane 1312 without blocking thetravel path of another vehicle (e.g., when AV 100 can join travel lane1312 at a safe distance behind vehicle 1302 a without blocking paths ofother vehicles).

While AV 100 waits at the primary stopline 1308, AV system 120 updatesthe expected travel path 1314 of vehicle 1302 a based on the movement ofvehicle 1302 a. As shown in FIG. 13B, vehicle 1302 a is turning into thetravel lane 1312 of AV 100 and the expected travel path 1314 is updatedto correspond to the turn. In some embodiments, AV system 120 determinesthe trajectory of vehicle 1302 a and updates the expected travel path1314 of vehicle 1302 a based on trajectory. In some embodiments, AVsystem 120 determines when vehicle 1302 a is expected to exit theintersection based on the trajectory.

As shown in FIG. 13C, once AV system 120 detects that the AV 100 isclear to safely merge into the travel lane 1312, AV system 120 instructsAV 100 to proceed past the primary stopline 1308. In some embodiments,before proceeding into the intersection, AV 100 stops (or slows) at asecondary stopline 1316. In some embodiments, the secondary stopline1316 corresponds to the near edge of the intersection. Moving past theprimary stopline 1308 to the secondary stopline 1316 before vehicle 1302a has exited the intersection indicates to other vehicles (e.g., vehicle1302 b) that AV 100 intends to proceed into the intersection. In someembodiments, when AV system 120 instructs AV 100 to AV proceed past theprimary stopline 1308 to the secondary stopline 1316, AV 100 isinstructed to accelerate with a predefined speed for indicating intentto proceed through intersection (e.g., a crawling speed that indicatesAV 100 will be next to go through the intersection).

While AV 100 is at the secondary stopline 1316, AV system 120 confirmsthat AV 100 is clear to safely merge into travel lane 1312 (e.g., noother vehicles are expected to intersect travel lane 1312). If anothervehicle is detected that poses a risk (e.g., a vehicle not currently atthe multi-way stop intersection that is traveling at a speed high enoughthat it is not expected to stop at the intersection), AV system 120instructs AV 100 to wait at the secondary stopline 1316 until AV 100 isclear to safely merge into the travel lane 1312. In some embodiments, AVsystem 120 determines whether any potential travel paths of undetectedvehicles (e.g., virtual vehicles that AV system 120 determines to betraveling toward intersection but cannot physically detect) wouldprevent AV 100 from safely merging into travel lane 1312.

In some embodiments, AV system 120 filters (e.g., disregards, ignores)other vehicles with expected travel paths that do not intersect with thetravel lane of the AV 100 (e.g., AV system 120 filters vehicle 1302 bwhen determining whether AV 100 should proceed past the secondarystopline 1316). In some embodiments, AV system 120 filters othervehicles moving below a threshold velocity or acceleration (e.g., AVsystem 120 disregards another vehicle that is crawling at a slow speedtoward the intersection).

As shown in FIG. 13D, after AV system 120 determines AV 100 can safelymerge into travel lane 1312, AV system 120 instructs AV 100 to proceedpast the secondary stopline 1316. In some embodiments, AV system 120confirms AV 100 is clear to safely merge into travel lane 1312 andinstructs AV 100 to proceed past the secondary stopline 1316 without theAV 100 stopping at the secondary stopline 1316. In some embodiments, AVsystem 120 determines that AV 100 is clear to safely merge into travellane 1312 when a distance between AV 100 and another vehicle (e.g.,vehicle 1302 a) traveling in the same direction in the travel lane 1312is greater than a threshold distance. In some embodiments, when AVsystem 120 instructs AV 100 to proceed past the secondary stopline 1316,AV 100 is instructed to accelerate with a predefined accelerationprofile through the intersection (e.g., a normal acceleration profileused with a standard “go” command).

FIG. 13E illustrates AV 100 waiting at primary stopline 1308 while twoother vehicles 1302 c and 1302 d are also at or near the multi-way stopintersection. Based on local traffic regulations, vehicle 1302 c has theprecedence at the intersection (e.g., vehicle 1302 c arrived at theintersection before vehicle 1302 d and AV 100). AV system 120 determinesthat vehicle 1302 a has the highest precedence and determines anexpected travel path 1314 of vehicle 1302 a. In some embodiments, theexpected travel path 1314 of vehicle 1302 c is based in part ondetecting a turn indicator of vehicle 1302 c. In the embodiment shown inFIG. 13E, a left turn indicator of vehicle 1302 c is detected, AV system120 determines that the expected travel path 1314 will cause vehicle1302 c to intersect the travel lane 1312 of AV 100. If AV 100 were toproceed into the intersection before vehicle 1302 c completes the turn,AV 100 would block the expected travel path 1314 of vehicle 1302 c. Insome embodiments, AV system 120 determines that AV 100 would block theexpected travel path of another vehicle when the other vehicle isexpected to change speed by more than a threshold change in speed toavoid colliding with AV 100 (e.g., when the other vehicle is expected todecelerate by more than 3.2 m/s′ to avoid colliding).

As shown in FIG. 13F, in response to the determination that the expectedtravel path 1314 of vehicle 1302 c will cause vehicle 1302 c tointersect the travel lane 1312 of AV 100, AV system 120 instructs AV 100to wait at the primary stopline 1308. AV 100 waits at the primarystopline 1308 until AV system 120 determines that the planned travelpath 1310 of AV 100 satisfies a set of one or more clearance criteria.The clearance criteria include a criterion that is satisfied when AV 100is clear to safely proceed along the travel lane 1312 without blockingthe travel path of another vehicle (e.g., when AV 100 can join thetravel lane 1312 without blocking the travel path of vehicle 1302 c).

While AV 100 waits at the primary stopline 1308, AV system 120 updatesthe expected travel path 1314 of vehicle 1302 c based on the movement ofvehicle 1302 c (e.g., vehicle 1302 c is expected to continue turning inthe same direction). As shown in FIG. 13F, vehicle 1302 c is turningleft across the travel lane 1312 of AV 100 and the expected travel path1314 is updated to correspond to the turn. In some embodiments, AVsystem 120 determines the trajectory of vehicle 1302 c and updates theexpected travel path 1314 of vehicle 1302 a based on trajectory. In someembodiments, the AV system 120 determines when vehicle 1302 c isexpected to exit the intersection based on the trajectory.

As shown in FIG. 13G, once AV system 120 detects that the expectedtravel path 1314 of vehicle 1302 c will cause vehicle 1302 c to exit thetravel lane 1312 (e.g., before vehicle 1302 c has exited theintersection), AV system 120 instructs AV 100 to proceed past theprimary stopline 1308. In some embodiments, before proceeding into theintersection, AV 100 stops (or slows) at a secondary stopline 1316corresponding to the near edge of the intersection. Moving past theprimary stopline 1308 to the secondary stopline 1316 before vehicle 1302c has exited the intersection indicates to other vehicles (e.g., vehicle1302 d) that AV 100 intends to proceed into the intersection. In someembodiments, when AV system 120 instructs AV 100 to AV proceed past theprimary stopline 1308 to the secondary stopline 1316, the AV 100 isinstructed to accelerate with a predefined speed for indicating intentto proceed through intersection (e.g., a crawling speed that indicatesthe AV 100 will be next to go through the intersection).

While stopped at or proceeding toward the secondary stopline 1316, AVsystem 120 confirms that AV 100 is clear to safely merge into travellane 1312 (e.g., no other vehicles are expected to intersect the travellane 1312). If another vehicle is detected that poses a risk (e.g., avehicle not currently at the multi-way stop intersection that istraveling at a speed high enough that it is not expected to stop at theintersection), AV system 120 instructs AV 100 to wait at the secondarystopline 1316 until AV 100 is clear to safely merge into the travel lane1312. In some embodiments, AV system 120 determines whether anypotential travel paths of undetected vehicles (e.g., virtual vehiclesthat AV system 120 determines to be traveling toward intersection butcannot physically detect) would prevent AV 100 from safely merging intothe travel lane 1312.

As shown in FIG. 13H, after AV system 120 determines AV 100 can safelymerge into the travel lane 1312 (e.g., vehicle 1302 c has exited thetravel lane 1312), AV system 120 instructs AV 100 to proceed past thesecondary stopline 1316. In some embodiments, AV system 120 confirms AV100 is clear to safely merge into the travel lane 1312 and instructs AV100 to proceed past the secondary stopline 1316 without AV 100 stoppingat the secondary stopline 1316. In some embodiments, when AV system 120instructs AV 100 to proceed past the secondary stopline 1316, AV 100 isinstructed to accelerate with a predefined acceleration profile throughthe intersection (e.g., a normal acceleration profile used with astandard “go” command).

FIG. 13I illustrates AV 100 waiting at primary stopline 1308 whileanother vehicle 1302 e is at or near the multi-way stop intersection. Asshown in FIG. 131, the planned travel path 1310 of AV 100 has AV 100turning left through the multi-way stop intersection. Based on theplanned travel path 1310, travel lane 1312 of AV 100 includes thecurrent lane of the roadway where the AV 100 is waiting at stopline 1308and a perpendicular lane of the roadway (e.g. the lane vehicle 1302 e isfacing).

Based on local traffic regulations, vehicle 1302 e has the precedence atthe intersection (e.g., vehicle 1302 e arrived at the intersectionbefore AV 100). AV system 120 determines that vehicle 1302 e has thehighest precedence and determines an expected travel path 1314 ofvehicle 1302 e. As shown in FIG. 131, AV system 120 initially determinesthe expected travel path 1314 of vehicle 1302 e will be straight towardthe intersection, which will cause vehicle 1302 e to intersect thetravel lane 1312 of AV 100.

As shown in FIG. 13J, in response to the determination that the expectedtravel path 1314 of vehicle 1302 e will cause vehicle 1302 e tointersect travel lane 1312 of AV 100, AV 100 waits at the primarystopline 1308. AV 100 waits at the primary stopline 1308 until AV system120 determines that the planned travel path 1310 of AV 100 satisfies aset of one or more clearance criteria. The clearance criteria include acriterion that is satisfied when AV 100 is clear to safely merge intothe travel lane 1312 without blocking the travel path of another vehicle(e.g., when AV 100 can join the travel lane 1312 at a safe distancebehind vehicle 1302 e without blocking paths of other vehicles).

While AV 100 waits at the primary stopline 1308, AV system 120 updatesthe expected travel path 1314 of vehicle 1302 c based on the movement ofvehicle 1302 e. As shown in FIG. 13J, vehicle 1302 e is continuingstraight into the travel lane 1312 of AV 100 and the expected travelpath 1314 is updated based on the continued direction of travel. In someembodiments, AV system 120 determines the trajectory of vehicle 1302 eand updates the expected travel path 1314 of vehicle 1302 a based ontrajectory. In some embodiments, AV system 120 determines when vehicle1302 e is expected to exit the intersection based on the trajectory.

As shown in FIG. 13K, once AV system 120 detects that the AV 100 isclear to safely proceed along the travel lane 1312, AV system 120instructs AV 100 to proceed past the primary stopline 1308. In someembodiments, before proceeding into the intersection, AV 100 stops (orslows) at a secondary stopline 1316 corresponding to the near edge ofthe intersection. Moving past the primary stopline 1308 to the secondarystopline 1316 before vehicle 1302 e has exited the intersectionindicates to other vehicles that AV 100 intends to proceed into theintersection. In some embodiments, when AV system 120 instructs AV 100to proceed past the primary stopline 1308 to the secondary stopline1316, AV 100 is instructed to accelerate with a predefined speed forindicating intent to proceed through intersection (e.g., a crawlingspeed that indicates the AV 100 will be next to go through theintersection).

While stopped at the secondary stopline 1316, AV system 120 confirmsthat AV 100 is clear to safely merge into the travel lane 1312 (e.g., noother vehicles are expected to intersect the travel lane 1312). Ifanother vehicle is detected that poses a risk (e.g., a vehicle notcurrently at the multi-way stop intersection that is traveling at aspeed high enough that it is not expected to stop at the intersection),AV system 120 instructs AV 100 to wait at the secondary stopline 1316until AV 100 is clear to safely merge into the travel lane 1312. In someembodiments, AV system 120 determines whether any potential travel pathsof undetected vehicles (e.g., virtual vehicles that AV system 120determines to be traveling toward intersection but cannot physicallydetect) would prevent AV 100 from safely merging into the travel lane1312.

As shown in FIG. 13L, after AV system 120 determines AV 100 can safelymerge into the travel lane 1312, AV system 120 instructs AV 100 toproceed past the secondary stopline 1316. In some embodiments, AV system120 confirms AV 100 is clear to safely merge into the travel lane 1312and instructs AV 100 to proceed past the secondary stopline 1316 withoutAV 100 stopping at the secondary stopline 1316. In some embodiments, AVsystem 120 determines that AV 100 is clear to safely merge into thetravel lane 1312 when a distance between the AV 100 and another vehicle(e.g., vehicle 1302 e) traveling in the same direction in the travellane 1312 is greater than a threshold distance. In some embodiments,when AV system 120 instructs AV 100 to proceed past the secondarystopline 1316, AV 100 is instructed to accelerate with a predefinedacceleration profile through the intersection (e.g., a normalacceleration profile used with a standard “go” command).

Example Processes for Navigating a Multi-Way Stop Intersection

FIG. 14 is a flow chart of an example process 1400 for navigating amulti-way stop intersection. For convenience, the process 1400 will bedescribed as being performed by a system of one or more computerslocated in one or more locations. For example, the AV system 120 of FIG.1 (or portions thereof), appropriately programmed in accordance withthis specification, can perform the process 1400.

At block 1402, while a first vehicle (e.g., AV 100) is operating in anautonomous mode (e.g., a fully or highly autonomous mode with automatedsteering, acceleration, braking, and navigation (e.g., Level 3, 4, or5)), the system (e.g., AV system 120) detects, using a processingcircuit, the first vehicle is at a primary stopline (e.g., 1308) (e.g.,a real or virtual line where a vehicle is expected to stop at anintersection (e.g., at the stop sign), a line corresponding to the nearedge of the intersection) of a multi-way stop intersection.

At block 1404, the system obtains, using the processing circuit, aplanned travel path though the multi-way stop intersection (e.g., 1310)(e.g., a path the AV 100 is expected to take from the stopline 1308 toan exit of the intersection based on the destination of the AV andcurrent road conditions). In some embodiments, the multi-way stopintersection includes a secondary stopline (e.g., 1316) in the plannedtravel path of the first vehicle. In some embodiments, the secondarystopline corresponds to an edge of the multi-way stop intersection.

In some embodiments, at block 1406, the system detects, using theprocessing circuit, one or more other vehicles (e.g., 1302 a-1302 e) atone or more tertiary stoplines (e.g., real or virtual lines where othervehicles are expected to stop at the intersection (e.g., at other stopsigns)) of the multi-way stop intersection.

At block 1408, the system determines whether the first vehicle has ahigher precedence than the one or more other vehicles at the one or moretertiary stoplines of the multi-way stop intersection (e.g., the AV 100is the next vehicle to have the right-of-way according to local trafficrules (e.g., the first vehicle arrived at the intersection before othervehicles at the intersection; the first vehicle is to the right ofanother vehicle that arrived at the intersection at approximately thesame time; the first vehicle going straight and another vehicle thatarrived at the intersection at approximately the same time is turning).

At block 1410, the system determines whether the planned travel path ofthe first vehicle through the multi-way stop intersection satisfies aset of one or more clearance criteria. The set of one or more clearancecriteria include a criterion that is satisfied in response to detectingthe first vehicle is clear to safely merge into a travel lane (e.g.,1312) (e.g., a lane of the roadway where vehicles travel in thedirection the AV 100 is planning to go) corresponding to (e.g.,overlapping, nearest to) the planned travel path (e.g., the AV 100 canjoin the travel lane 1312 at a safe distance behind another vehicletraveling along the same path, and without blocking paths of othervehicles). In some embodiments, detecting the first vehicle is clear tosafely merge into the travel lane includes detecting the first vehicledoes not block an expected travel path of another vehicle. In someembodiments, the first vehicle does not block the expected travel pathof another vehicle when the other vehicle is not expected to changespeed by more than a threshold change in speed (e.g., the other vehicleis not expected to decelerate by more than 3.2 m/s²). In someembodiments, detecting the first vehicle is clear to safely merge intothe travel lane includes detecting a distance between the first vehicleand another vehicle in the travel lane is greater than a thresholddistance. In some embodiments, the expected travel path of the othervehicle corresponds to a potential travel path of an undetected vehicle(e.g., virtual vehicle that AV system 120 determines to be travelingtoward intersection but cannot physically detect).

In some embodiments, the system detects, using the processing circuit,one or more other vehicles with expected travel paths that do notintersect with the travel lane of the first vehicle and filters (e.g.,disregards, ignores), using the processing circuit, the one or moreother vehicles from the determination that the planned travel path ofthe first vehicle through the multi-way stop intersection satisfies aset of one or more clearance criteria. In some embodiments, the set ofone or more clearance criteria include a criterion that is not satisfiedif another vehicle with a speed more than a threshold speed is detectedapproaching the multi-way stop intersection (e.g., other vehicle istraveling at a speed high enough that it is not expected to stop at itsown stopline of the multi-stop intersection).

At block 1412, in accordance with a determination that the first vehiclehas a higher precedence than the one or more other vehicles at the oneor more tertiary stoplines of the multi-way stop intersection and inaccordance with the determination that the planned travel path of thefirst vehicle through the multi-way stop intersection satisfies the setof one or more clearance criteria, the system instructs, using thecontrol circuit, the first vehicle to proceed past the primary stopline(e.g., travel into the intersection, travel to another stopline (e.g.,1316) at a near edge of the intersection).

In some embodiments, after instructing the first vehicle to proceed pastthe primary stopline, the system detects, using the processing circuit,one or more other vehicles at one or more tertiary stoplines (e.g., realor virtual lines where other vehicles are expected to stop at theintersection (e.g., at other stop signs)) of the multi-way stopintersection. In accordance with a determination that the first vehiclehas a higher precedence than the one or more other vehicles at the oneor more tertiary stoplines of the multi-way stop intersection (e.g., theAV 100 is the next vehicle to have the right-of-way according to localtraffic rules) and in accordance with the determination that the plannedtravel path of the first vehicle through the multi-way stop intersectionsatisfies the set of one or more clearance criteria, the systeminstructs, using the control circuit, the first vehicle to proceed pastthe secondary stopline. In accordance with a determination that thefirst vehicle does not have a higher precedence than at least one of theone or more other vehicles at the one or more tertiary stoplines of themulti-way stop intersection or in accordance with a determination thatthe planned travel path of the first vehicle through the multi-way stopintersection does not satisfy the set of one or more clearance criteria,the system instructs, using the control circuit, the first vehicle toforgo proceeding past the secondary stopline (e.g., the AV 100 waits atthe secondary stopline 1316). In some embodiments, instructing the firstvehicle to forgo proceeding past the secondary stopline includesinstructing the first vehicle to stop at the secondary stopline.

At block 1414, in accordance with a determination that the first vehicledoes not have a higher precedence than at least one of the one or moreother vehicles at the one or more tertiary stoplines of the multi-waystop intersection or in accordance with a determination that the plannedtravel path of the first vehicle through the multi-way stop intersectiondoes not satisfy the set of one or more clearance criteria, the systeminstructs, using the control circuit, the first vehicle to forgoproceeding past the primary stopline (e.g., the AV 100 waits at theprimary stopline 1308).

FIG. 15 is a flow chart of an example process 1500 for navigating amulti-way stop intersection. For convenience, the process 1500 will bedescribed as being performed by a system of one or more computerslocated in one or more locations. For example, the AV system 120 of FIG.1 (or portions thereof), appropriately programmed in accordance withthis specification, can perform the process 1500.

At block 1502, while a first vehicle (e.g., AV 100) is operating in anautonomous mode (e.g., a fully or highly autonomous mode with automatedsteering, acceleration, braking, and navigation (e.g., Level 3, 4, or5)) at a multi-way stop intersection and has a highest precedence (e.g.,the AV 100 is the next vehicle to have the right-of-way according tolocal traffic rules (e.g., the first vehicle arrived at the intersectionbefore other vehicles at the intersection; the first vehicle is to theright of another vehicle that arrived at the intersection atapproximately the same time; the first vehicle going straight andanother vehicle that arrived at the intersection at approximately thesame time is turning)) at the multi-way stop intersection, the system(e.g., AV system 120) detects, using a processing circuit, movement of asecond vehicle (e.g., 1302 a-1302 e) at the intersection (e.g., at ornear a stop sign; in the intersection at an area where travel pathsintersect). In some embodiments, detecting the movement of the secondvehicle includes detecting a velocity of the second vehicle, and inaccordance with a determination that the velocity of the second vehicleis below a threshold velocity (e.g., the other vehicle is crawlingtoward intersection), the system instructs, using the control circuit,the first vehicle to proceed into the intersection. In some embodiments,in accordance with a determination that the velocity of the secondvehicle is at or above the threshold velocity, the system forgoesinstructing the first vehicle to proceed into the intersection. In someembodiments, detecting the movement of the second vehicle includesdetecting an acceleration of the second vehicle, and in accordance witha determination that the acceleration of the second vehicle is below athreshold acceleration (e.g., the other vehicle is crawling towardintersection), the system instructs, using the control circuit, thefirst vehicle to proceed into the intersection. In some embodiments, inaccordance with a determination that the acceleration of the secondvehicle is at or above the threshold acceleration, the system forgoesinstructing the first vehicle to proceed into the intersection.

At block 1504, the system determines the second vehicle has an expectedtravel path (e.g., 1314) through the intersection that intersects aplanned travel path (e.g., 1310) of the first vehicle through theintersection (e.g., based on detecting a turn signal of the secondvehicle, based on a calculated trajectory of the second vehicle).

At block 1506, in accordance with a determination, based on the detectedmovement of the second vehicle, that the second vehicle is expected toexit the intersection (e.g., before the first vehicle can reach a pointon the expected travel path of the second vehicle) (e.g., proceedinginto the intersection by the first vehicle will not cause a collisionwith the second vehicle based on the expected and planned travel paths),the system instructs, using a control circuit, the first vehicle toproceed into the intersection before the second vehicle exits theintersection. In some embodiments, the determination, based on thedetected movement of the second vehicle, that the second vehicle isexpected to exit the intersection includes determining the trajectory ofthe second vehicle. In some embodiments, in accordance with adetermination that the trajectory of the second vehicle does notintersect an expected trajectory of the first vehicle, the systeminstructs, using the control circuit, the first vehicle to proceed intothe intersection before the second vehicle exits the intersection.

In some embodiments, after proceeding into the intersection and inaccordance with a determination that the trajectory of the secondvehicle intersects an expected trajectory of the first vehicle, thesystem instructs, using the control circuit, the first vehicle to stopbefore the first vehicle exits the intersection (e.g., after beginningmovement toward intersection, the AV 100 stops if a trajectory ofanother vehicle predicted to intersect with the AV's trajectory). Insome embodiments, instructing the first vehicle to proceed into theintersection includes instructing the first vehicle to accelerate with apredefined acceleration curve through the intersection (e.g., a normalacceleration curve used with standard “go” command). In someembodiments, instructing the first vehicle to proceed into theintersection includes instructing the first vehicle to proceed with apredefined speed for indicating intent to proceed through intersection(e.g., a crawling speed that indicates the first vehicle will be next togo through intersection). In some embodiments, after instructing thefirst vehicle to proceed with the predefined speed for indicatingintent, the system instructs, using the control circuit, the firstvehicle to accelerate with a predefined acceleration curve (e.g., anormal acceleration curve used with standard “go” command).

In the foregoing description, embodiments have been described withreference to numerous specific details that may vary from implementationto implementation. The description and drawings are, accordingly, to beregarded in an illustrative rather than a restrictive sense. The soleand exclusive indicator of the scope of the claims, and what is intendedby the applicants to be the scope of the claims, is the literal andequivalent scope of the set of claims that issue from this application,in the specific form in which such claims issue, including anysubsequent correction. Any definitions expressly set forth herein forterms contained in such claims shall govern the meaning of such terms asused in the claims. In addition, when we use the term “furthercomprising,” in the foregoing description or following claims, whatfollows this phrase can be an additional step or entity, or asub-step/sub-entity of a previously-recited step or entity.

What is claimed is:
 1. A system comprising one or more computerprocessors; and one or more non-transitory storage media storinginstructions which, when executed by the one or more computerprocessors, cause performance of operations comprising: while a firstvehicle is operating in an autonomous mode: detecting, using aprocessing circuit, the first vehicle is at a primary stopline of amulti-way stop intersection; obtaining, using the processing circuit, aplanned travel path though the multi-way stop intersection; and inresponse to detecting that the first vehicle is at a primary stopline ofa multi-way stop intersection: in accordance with a determination thatthe planned travel path of the first vehicle through the multi-way stopintersection satisfies a set of one or more clearance criteria,instructing, using a control circuit, the first vehicle to proceed pastthe primary stopline, wherein the set of one or more clearance criteriainclude a criterion that is satisfied in response to detecting the firstvehicle is clear to safely merge into a travel lane corresponding to theplanned travel path; and in accordance with a determination that theplanned travel path of the first vehicle through the multi-way stopintersection does not satisfy the set of one or more clearance criteria,instructing, using the control circuit, the first vehicle to forgoproceeding past the primary stopline.
 2. The system of claim 1, whereinthe instructions further cause performance of operations comprising: inresponse to detecting that the first vehicle is at the primary stoplineof the multi-way stop intersection: detecting, using the processingcircuit, one or more other vehicles at one or more tertiary stoplines ofthe multi-way stop intersection; and in accordance with a determinationthat the first vehicle has a higher precedence than the one or moreother vehicles at the one or more tertiary stoplines of the multi-waystop intersection and in accordance with the determination that theplanned travel path of the first vehicle through the multi-way stopintersection satisfies the set of one or more clearance criteria,instructing, using the control circuit, the first vehicle to proceedpast the primary stopline; and in accordance with a determination thatthe first vehicle does not have a higher precedence than at least one ofthe one or more other vehicles at the one or more tertiary stoplines ofthe multi-way stop intersection or in accordance with a determinationthat the planned travel path of the first vehicle through the multi-waystop intersection does not satisfy the set of one or more clearancecriteria, instructing, using the control circuit, the first vehicle toforgo proceeding past the primary stopline.
 3. The system of claim 1,wherein detecting the first vehicle is clear to safely merge into thetravel lane includes detecting the first vehicle does not block anexpected travel path of another vehicle.
 4. The system of claim 3,wherein the first vehicle does not block the expected travel path ofanother vehicle when the other vehicle is not expected to change speedby more than a threshold change in speed.
 5. The system of claim 1,wherein detecting the first vehicle is clear to safely merge into thetravel lane includes detecting a distance between the first vehicle andanother vehicle in the travel lane is greater than a threshold distance.6. The system of claim 3, wherein the expected travel path of the othervehicle corresponds to a potential travel path of an undetected vehicle.7. The system of claim 1, wherein the multi-way stop intersectionincludes a secondary stopline in the planned travel path of the firstvehicle.
 8. The system of claim 7, wherein the secondary stoplinecorresponds to an edge of the multi-way stop intersection.
 9. The systemof claim 7, wherein the instructions further cause performance ofoperations comprising: after instructing the first vehicle to proceedpast the primary stopline: detecting, using the processing circuit, oneor more other vehicles at one or more tertiary stoplines of themulti-way stop intersection; and in accordance with a determination thatthe first vehicle has a higher precedence than the one or more othervehicles at the one or more tertiary stoplines of the multi-way stopintersection and in accordance with the determination that the plannedtravel path of the first vehicle through the multi-way stop intersectionsatisfies the set of one or more clearance criteria, instructing, usingthe control circuit, the first vehicle to proceed past the secondarystopline; and in accordance with a determination that the first vehicledoes not have a higher precedence than at least one of the one or moreother vehicles at the one or more tertiary stoplines of the multi-waystop intersection or in accordance with a determination that the plannedtravel path of the first vehicle through the multi-way stop intersectiondoes not satisfy the set of one or more clearance criteria, instructing,using the control circuit, the first vehicle to forgo proceeding pastthe secondary stopline.
 10. The system of claim 9, wherein instructingthe first vehicle to forgo proceeding past the secondary stoplineincludes instructing the first vehicle to stop at the secondarystopline.
 11. The system of claim 1, wherein the instructions furthercause performance of operations comprising: detecting, using theprocessing circuit, one or more other vehicles with expected travelpaths that do not intersect with the travel lane of the first vehicle;and filtering, using the processing circuit, the one or more othervehicles from the determination that the planned travel path of thefirst vehicle through the multi-way stop intersection satisfies a set ofone or more clearance criteria.
 12. The system of claim 1, wherein theset of one or more clearance criteria include a criterion that is notsatisfied if another vehicle with a speed more than a threshold speed isdetected approaching the multi-way stop intersection.
 13. A method,comprising: while a first vehicle is operating in an autonomous mode:detecting, using a processing circuit, the first vehicle is at a primarystopline of a multi-way stop intersection; obtaining, using theprocessing circuit, a planned travel path though the multi-way stopintersection; and in response to detecting that the first vehicle is ata primary stopline of a multi-way stop intersection: in accordance witha determination that the planned travel path of the first vehiclethrough the multi-way stop intersection satisfies a set of one or moreclearance criteria, instructing, using a control circuit, the firstvehicle to proceed past the primary stopline, wherein the set of one ormore clearance criteria include a criterion that is satisfied inresponse to detecting the first vehicle is clear to safely merge into atravel lane corresponding to the planned travel path; and in accordancewith a determination that the planned travel path of the first vehiclethrough the multi-way stop intersection does not satisfy the set of oneor more clearance criteria, instructing, using the control circuit, thefirst vehicle to forgo proceeding past the primary stopline.
 14. Themethod of claim 13, further comprising: in response to detecting thatthe first vehicle is at the primary stopline of the multi-way stopintersection: detecting, using the processing circuit, one or more othervehicles at one or more tertiary stoplines of the multi-way stopintersection; and in accordance with a determination that the firstvehicle has a higher precedence than the one or more other vehicles atthe one or more tertiary stoplines of the multi-way stop intersectionand in accordance with the determination that the planned travel path ofthe first vehicle through the multi-way stop intersection satisfies theset of one or more clearance criteria, instructing, using the controlcircuit, the first vehicle to proceed past the primary stopline; and inaccordance with a determination that the first vehicle does not have ahigher precedence than at least one of the one or more other vehicles atthe one or more tertiary stoplines of the multi-way stop intersection orin accordance with a determination that the planned travel path of thefirst vehicle through the multi-way stop intersection does not satisfythe set of one or more clearance criteria, instructing, using thecontrol circuit, the first vehicle to forgo proceeding past the primarystopline.
 15. The method of claim 13, wherein detecting the firstvehicle is clear to safely merge into the travel lane includes detectingthe first vehicle does not block an expected travel path of anothervehicle.
 16. The method of claim 15, wherein the first vehicle does notblock the expected travel path of another vehicle when the other vehicleis not expected to change speed by more than a threshold change inspeed.
 17. The method of claim 13, wherein detecting the first vehicleis clear to safely merge into the travel lane includes detecting adistance between the first vehicle and another vehicle in the travellane is greater than a threshold distance.
 18. The method of claim 13,wherein the multi-way stop intersection includes a secondary stopline inthe planned travel path of the first vehicle.
 19. The method of claim18, wherein the secondary stopline corresponds to an edge of themulti-way stop intersection.
 20. One or more non-transitory storagemedia storing instructions which, when executed by one or more computingdevices, cause performance of operations comprising: detecting, using aprocessing circuit, the first vehicle is at a primary stopline of amulti-way stop intersection; obtaining, using the processing circuit, aplanned travel path though the multi-way stop intersection; and inresponse to detecting that the first vehicle is at a primary stopline ofa multi-way stop intersection: in accordance with a determination thatthe planned travel path of the first vehicle through the multi-way stopintersection satisfies a set of one or more clearance criteria,instructing, using a control circuit, the first vehicle to proceed pastthe primary stopline, wherein the set of one or more clearance criteriainclude a criterion that is satisfied in response to detecting the firstvehicle is clear to safely merge into a travel lane corresponding to theplanned travel path; and in accordance with a determination that theplanned travel path of the first vehicle through the multi-way stopintersection does not satisfy the set of one or more clearance criteria,instructing, using the control circuit, the first vehicle to forgoproceeding past the primary stopline.